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The objective of this study is to establish a geographical information system method for spatial assessment of soil erosion based on the universal soil loss equation (USLE), and to evaluate the utility of GIS with regard to soil erosion mapping. The study area, Goynuk, covers 1,437 square kilometers and is located in the southeastern part of Bolu, Turkey. In this study, USLE factors including rainfall erosivity (R-factor), soil erodibility (K-factor), slope and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (Pfactor) were studied and reviewed. Each factor, which consists of a set of logically related geographic features and attributes, was used as an input for analysis. A land use map of the study area was generated from (Landsat TM 2000) satellite imagery. A digital elevation model (DEM) interpolated from elevation contours was used to generate the slope and LS-factor. Spatial vegetative cover, extracted from Landsat TM imagery, was used to determine the spatial C-factor and P-factor, values of which are based on experimental results from the literature. USLE model calculation applied to the resultant polygonal layer gave values of soil loss in tons/ha/year. These are then ranked into three classes as low, moderate, and high. The study indicated that highly eroded areas are bare lands and steep conditions, whereas less eroded areas are low slope classes. As a conclusion the study confirms that the use of GIS and remotely sensed data can greatly enhance spatial modeling for soil erosion.
The study aimed at identifying and mapping groundwater potential zones in agricultural intensive Sarada river basin using Remote sensing and GIS technology. Zones of water potentiality were mapped integrating various information layers in GIS environment which eventually helped weighted modeling to arrive at the final outcome. Hydrogeomorphic units such as alluvial plains, valley fills, shallow weathered pediplains and deeply weathered pediplains were mapped. Eventually water potential zones in the basin were mapped and categorised them in to ‘excellent’, ‘good’, ‘moderate’ and ‘poor’. The study highlighted the effective use of Remote sensing and GIS technology for integrated analysis, identification and mapping of the groundwater potential zones in the Sarada river basin.
Sub-basins prioritization is one of the most important resolutions of development sustainability and natural resources comprehended management. In this study, 11 sub-basins of Lohender in east Golstan province about 272/63cm Prioritized using computation and morphometric analysis and using GIS and RS techniques. Erosion mode in each sub-basin specified through Sediment Yield Index approximation. In morphometric analysis, parameters like canal length, bifurcation ratio, discharge density, sub-basins shape coefficient, round coefficient, stretch coefficient and compressive coefficients were computed thus these parameters divided to two classifications: linear coefficients and figurative coefficient. In order to study annual sediment index, from fields applied maps, land coverage, slope, soil type and topographic map scale 1:50000 were used. Finally, each sub-basin Priority determined due to Sediment Yield Index (SYI) and total average of morphometric parameters. According to morphometric parameters, the BS sub-basin and according to SYI parameter, A5 sub-basin showed more critical mode and combination of both showed that B2 sub-basin showed the worst situation.
The aim of presented studies was the use of aerial photography to determine long-term permanent areas of weed infestation. Aerial photos are becoming a more available form of information on spatial diversity of agricultural field production. They are commonly used for drawing application maps, which are the basis for precision farming. Available GIS (geographical information system) tools enables rectification of aerial photos, which were taken by digital cameras. Consequently, the prepared photomaterials can then be analysed by geo-processing operations. Weed infestation of a given field, especially visible in latter stages of crops in the growing season, allows relatively easy to identify large, dispersed, and small clusters of weeds. Comparing aerial photos taken over a certain amount of years, allows to develop strategies of active (target) plant protection. The paper presents a low-altitude remote sensing method and stages of persistent weed infestation, including zones of mapping for precision farming. The fields of winter wheat and winter rape of the ZD IUNG – PIB Osiny (51°27’N, 22°1’E), were photographed in the period of 2005–2007.
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